{"id":"W7022585777","doi":"","title":"The Uber Effect","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Unemployment; Falling (accident); Population; Unemployment rate; Control (management); Term (time); Variable (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003515696,0.0006994012,0.001256327,0.001525377,0.001298272,0.00208914,0.0008430977,0.00176044,0.05365288],"category_scores_gemma":[0.01340892,0.0003728207,0.00130373,0.001710215,0.001740791,0.002629572,0.002451428,0.002266838,0.00454386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001318961,"about_ca_system_score_gemma":0.001352401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01673898,"about_ca_topic_score_gemma":0.0138251,"domain_scores_codex":[0.9957963,0.001131527,0.0002152896,0.001159847,0.0008706034,0.0008264227],"domain_scores_gemma":[0.9842193,0.007317768,0.005129445,0.001314858,0.001142449,0.0008762575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008301475,0.0008121993,0.5787547,0.0004073198,0.001063439,0.0009083015,0.001595129,0.007389627,0.000798176,0.1974449,0.0358577,0.1741384],"study_design_scores_gemma":[0.0003469066,0.001369579,0.7042535,0.0005058369,0.001244741,0.0007570495,0.003317109,0.01385938,0.002309869,0.1074308,0.1644422,0.0001630683],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5339942,0.00977689,0.03823049,0.01580434,0.001135821,0.0006214247,0.006227667,0.0008264051,0.3933827],"genre_scores_gemma":[0.9397075,0.002142685,0.001470822,0.002391581,0.0004123466,0.00013514,0.0008117739,0.00006525166,0.05286304],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05365288,"threshold_uncertainty_score":0.1794868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04402631206432242,"score_gpt":0.2776794149187135,"score_spread":0.233653102854391,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}